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Annotation 7625579302156

[unknown IMAGE 7101511240972]

#has-images #recurrent-neural-networks #rnn

This particular customer history can then be represented as a sequence of vectors with five elements: the input variable plus the four covariates. Individual-level covariates are strictly optional

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This particular customer history can then be represented as a sequence of vectors with five elements: the input variable plus the four covariates. Individual-level covariates are strictly optional – in our empirical study, the Base model is built without any such variables. Whenever individual covariates are included, we label the model Extended. Note that the model is completely

Original toplevel document (pdf)

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Flashcard 7625581137164

Tags

#feature-engineering #lstm #recurrent-neural-networks #rnn

Question

While an [...] can carry forward useful information from one timestep to the next, however, it is much less effective at capturing long-term dependencies (Bengio, Simard, & Frasconi, 1994; Pascanu, Mikolov, & Bengio, 2013). This limitation turns out to be a crucial problem in marketing analytics.

Answer

RNN

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While an RNN can carry forward useful information from one timestep to the next, however, it is much less effective at capturing long-term dependencies (Bengio, Simard, & Frasconi, 1994; Pascanu

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Annotation 7625614691596

Different shapes of the tensors

#tensorflow #tensorflow-certificate

y_test.shape, y_pred.shape, y_pred.reshape((10, )).shape, tf.squeeze(y_pred).shape


(TensorShape([10]), (10, 1), (10,), TensorShape([10]))

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Flashcard 7625617837324

Tags

#tensorflow #tensorflow-certificate

Question

y_test.shape, y_pred.shape, y_pred.reshape((10, )).shape, [...](y_pred).shape


(TensorShape([10]), (10, 1), (10,), TensorShape([10]))

Answer

tf.squeeze

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scheduled repetition interval		last repetition or drill

Different shapes of the tensors
y_test.shape, y_pred.shape, y_pred.reshape((10, )).shape, tf.squeeze(y_pred).shape (TensorShape([10]), (10, 1), (10,), TensorShape([10]))

Flashcard 7625619410188

Tags

#tensorflow #tensorflow-certificate

Question

y_test.shape, y_pred.shape, y_pred.[...]((10, )).shape, tf.squeeze(y_pred).shape


(TensorShape([10]), (10, 1), (10,), TensorShape([10]))

Answer

reshape

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scheduled repetition interval		last repetition or drill

Different shapes of the tensors
y_test.shape, y_pred.shape, y_pred.reshape((10, )).shape, tf.squeeze(y_pred).shape (TensorShape([10]), (10, 1), (10,), TensorShape([10]))

Flashcard 7625620720908

Tags

#tensorflow #tensorflow-certificate

Question

y_test.shape, y_pred.shape, y_pred.reshape([...]).shape, tf.squeeze(y_pred).shape


(TensorShape([10]), (10, 1), (10,), TensorShape([10]))

Answer

(10, )

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scheduled repetition interval		last repetition or drill

Different shapes of the tensors
y_test.shape, y_pred.shape, y_pred.reshape((10, )).shape, tf.squeeze(y_pred).shape (TensorShape([10]), (10, 1), (10,), TensorShape([10]))

Flashcard 7625622031628

Tags

#tensorflow #tensorflow-certificate

Question

y_test.shape, y_pred.shape, y_pred.reshape((10, )).shape, tf.squeeze(y_pred).shape


(TensorShape([10]), (10, 1), (10,), [...])

Answer

TensorShape([10])

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scheduled repetition interval		last repetition or drill

Different shapes of the tensors
y_test.shape, y_pred.shape, y_pred.reshape((10, )).shape, tf.squeeze(y_pred).shape (TensorShape([10]), (10, 1), (10,), TensorShape([10]))

Flashcard 7625623604492

Tags

#tensorflow #tensorflow-certificate

Question

y_test.shape, y_pred.shape, y_pred.reshape((10, )).shape, tf.squeeze(y_pred).shape


(TensorShape([10]), (10, 1), [...], TensorShape([10]))

Answer

(10,)

status	not learned	measured difficulty	37% [default]	last interval [days]
repetition number in this series	0	memorised on		scheduled repetition
scheduled repetition interval		last repetition or drill

Different shapes of the tensors
y_test.shape, y_pred.shape, y_pred.reshape((10, )).shape, tf.squeeze(y_pred).shape (TensorShape([10]), (10, 1), (10,), TensorShape([10]))

Annotation 7625624915212

Calculate MSE "by hand" in steps - identify functions

#tensorflow #tensorflow-certificate

# Calculate MSE "by hand" in steps - identify functions

abs_err = tf.abs(tf.subtract(tf.cast(y_test, dtype=tf.float32), tf.squeeze(y_pred)))
sq_abs_err = tf.multiply(abs_err, abs_err)
sq_abs_err
tf.math.reduce_mean(sq_abs_err)



<tf.Tensor: shape=(), dtype=float32, numpy=155.11417>

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Flashcard 7625626750220

Tags

#tensorflow #tensorflow-certificate

Question

# Calculate MSE "by hand" in steps - identify functions

abs_err = tf.abs(tf.subtract(tf.cast(y_test, dtype=tf.float32), tf.squeeze(y_pred)))
sq_abs_err = tf.multiply(abs_err, abs_err)
sq_abs_err
tf.math.[...](sq_abs_err)



<tf.Tensor: shape=(), dtype=float32, numpy=155.11417>

Answer

reduce_mean

status	not learned	measured difficulty	37% [default]	last interval [days]
repetition number in this series	0	memorised on		scheduled repetition
scheduled repetition interval		last repetition or drill

Calculate MSE "by hand" in steps - identify functions
te MSE "by hand" in steps - identify functions abs_err = tf.abs(tf.subtract(tf.cast(y_test, dtype=tf.float32), tf.squeeze(y_pred))) sq_abs_err = tf.multiply(abs_err, abs_err) sq_abs_err tf.math.<span>reduce_mean(sq_abs_err) <tf.Tensor: shape=(), dtype=float32, numpy=155.11417> <span>

Flashcard 7625628323084

Tags

#tensorflow #tensorflow-certificate

Question

# Calculate MSE "by hand" in steps - identify functions

abs_err = [...](tf.subtract(tf.cast(y_test, dtype=tf.float32), tf.squeeze(y_pred)))
sq_abs_err = tf.multiply(abs_err, abs_err)
sq_abs_err
tf.math.reduce_mean(sq_abs_err)



<tf.Tensor: shape=(), dtype=float32, numpy=155.11417>

Answer

tf.abs

status	not learned	measured difficulty	37% [default]	last interval [days]
repetition number in this series	0	memorised on		scheduled repetition
scheduled repetition interval		last repetition or drill

Calculate MSE "by hand" in steps - identify functions
# Calculate MSE "by hand" in steps - identify functions abs_err = tf.abs(tf.subtract(tf.cast(y_test, dtype=tf.float32), tf.squeeze(y_pred))) sq_abs_err = tf.multiply(abs_err, abs_err) sq_abs_err tf.math.reduce_mean(sq_abs_err) <tf.Tensor: shape=(), dtype=

Flashcard 7625629371660

Tags

#tensorflow #tensorflow-certificate

Question

# Calculate MSE "by hand" in steps - identify functions

abs_err = tf.abs(tf.subtract([...](y_test, dtype=tf.float32), tf.squeeze(y_pred)))
sq_abs_err = tf.multiply(abs_err, abs_err)
sq_abs_err
tf.math.reduce_mean(sq_abs_err)



<tf.Tensor: shape=(), dtype=float32, numpy=155.11417>

Answer

tf.cast

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Flashcard 7625630420236

Tags

#tensorflow #tensorflow-certificate

Question

# Calculate MSE "by hand" in steps - identify functions

abs_err = tf.abs([...](tf.cast(y_test, dtype=tf.float32), tf.squeeze(y_pred)))
sq_abs_err = tf.multiply(abs_err, abs_err)
sq_abs_err
tf.math.reduce_mean(sq_abs_err)



<tf.Tensor: shape=(), dtype=float32, numpy=155.11417>

Answer

tf.subtract

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repetition number in this series	0	memorised on		scheduled repetition
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Flashcard 7625631468812

Tags

#tensorflow #tensorflow-certificate

Question

# Calculate MSE "by hand" in steps - identify functions

abs_err = tf.abs(tf.subtract(tf.cast(y_test, dtype=tf.float32), tf.squeeze(y_pred)))
sq_abs_err = tf.multiply(abs_err, abs_err)
sq_abs_err
tf.[...](sq_abs_err)  # mean squared error



<tf.Tensor: shape=(), dtype=float32, numpy=155.11417>

Answer

math.reduce_mean

status	not learned	measured difficulty	37% [default]	last interval [days]
repetition number in this series	0	memorised on		scheduled repetition
scheduled repetition interval		last repetition or drill

Calculate MSE "by hand" in steps - identify functions
lculate MSE "by hand" in steps - identify functions abs_err = tf.abs(tf.subtract(tf.cast(y_test, dtype=tf.float32), tf.squeeze(y_pred))) sq_abs_err = tf.multiply(abs_err, abs_err) sq_abs_err tf.<span>math.reduce_mean(sq_abs_err) <tf.Tensor: shape=(), dtype=float32, numpy=155.11417> <span>

Annotation 7625638022412

[unknown IMAGE 7625638546700]

Visualize model

#has-images #tensorflow #tensorflow-certificate

plot_model(model_2, show_shapes=True)

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Flashcard 7625641692428

Tags

#has-images #tensorflow #tensorflow-certificate

[unknown IMAGE 7625638546700]

Question

plot_model(model_2, [...])

Answer

show_shapes=True

status	not learned	measured difficulty	37% [default]	last interval [days]
repetition number in this series	0	memorised on		scheduled repetition
scheduled repetition interval		last repetition or drill

Visualize model
plot_model(model_2, show_shapes=True)

Flashcard 7625643265292

Tags

#has-images #tensorflow #tensorflow-certificate

[unknown IMAGE 7625638546700]

Question

[...](model_2, show_shapes=True)

Answer

plot_model

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repetition number in this series	0	memorised on		scheduled repetition
scheduled repetition interval		last repetition or drill

Visualize model
plot_model(model_2, show_shapes=True)

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on 27-Apr-2024 (Sat)

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Original toplevel document (pdf)

Parent (intermediate) annotation

Original toplevel document (pdf)